The Internet is a global system of interconnected computers and computer networks that use a standard Internet protocol suite (e.g., the Transmission Control Protocol (TCP) and Internet Protocol (IP)) to communicate with each other. The Internet of Things (IoT) is based on the idea that everyday objects, not just computers and computer networks, can be readable, recognizable, locatable, addressable, and controllable via an IoT communications network (e.g., an ad-hoc network or the Internet).
A number of market trends are driving development of IoT devices. For example, increasing energy costs are driving governments' strategic investments in smart grids and support for future consumption, such as for electric vehicles and public charging stations. Increasing health care costs and aging populations are driving development for remote/connected health care and fitness services. A technological revolution in the home is driving development for new “smart” services, including consolidation by service providers marketing ‘N’ play (e.g., data, voice, video, security, energy management, etc.) and expanding home networks. Buildings are getting smarter and more convenient as a means to reduce operational costs for enterprise facilities.
There are a number of key applications for the IoT. For example, in the area of smart grids and energy management, utility companies can optimize delivery of energy to homes and businesses while customers can better manage energy usage. In the area of home and building automation, smart homes and buildings can have centralized control over virtually any device or system in the home or office, from appliances to plug-in electric vehicle (PEV) security systems. In the field of asset tracking, enterprises, hospitals, factories, and other large organizations can accurately track the locations of high-value equipment, patients, vehicles, and so on. In the area of health and wellness, doctors can remotely monitor patients' health while people can track the progress of fitness routines. As such, in the near future, increasing development in IoT technologies will lead to numerous IoT devices surrounding a user at home, in vehicles, at work, and many other locations. However, despite the fact that IoT capable devices can provide substantial real-time information about the environment surrounding a user (e.g., likes, choices, habits, device conditions and usage patterns, etc.), known conventional personal recommendation engines typically lack the ability to adequately monitor, aggregate, filter, and otherwise process all available information that may be relevant to providing personalized recommendations to users. For example, known conventional personal recommendation engines typically provide recommendations based on user online purchase histories and correlations with other users who may have purchased or expressed interest in similar items based on knowledge from only one or a limited set of online sites (e.g., Amazon.com or Overstock.com). The recommendations that existing engines provide therefore tend to be limited in that the recommendations are based on a small set of products or services that the user bought from that online site and therefore may not be the best or most relevant recommendation to the user. Furthermore, because existing recommendation engines typically do not know whether a purchased item was bought for the user or as a gift for someone else, any future recommendations to the user that are based on that item may not be particularly relevant.
Accordingly, a need exists for a recommendation engine that can provide personal recommendations having contextual relevance based on real-time knowledge about the environment surrounding a user and the things that the user has and interacts with therein.